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Control of a Robot Arm Using Decoded Joint Angles from Electrocorticograms in Primate
2018
Computational Intelligence and Neuroscience
Electrocorticogram (ECoG) is a well-known recording method for the less invasive brain machine interface (BMI). Our previous studies have succeeded in predicting muscle activities and arm trajectories from ECoG signals. Despite such successful studies, there still remain solving works for the purpose of realizing an ECoG-based prosthesis. We suggest a neuromuscular interface to control robot using decoded muscle activities and joint angles. We used sparse linear regression to find the best fit
doi:10.1155/2018/2580165
pmid:30420874
pmcid:PMC6211210
dblp:journals/cin/ShinKYK18
fatcat:e73ekponanebbdgrnqhg5yizra